agentpdf

agentpdf

[!WARNING] This is a vibe-coded tool. The code was briefly reviewed by a human but not directly changed / maintained manually.

Make large PDFs — specifications, reference manuals, datasheets — usable by AI coding agents without reading them into context.

agentpdf converts a PDF once into small Markdown section files, images of its tables and figures, a table of contents and a full-text search index. Agents then search and read only the parts they need, with their usual tools.

uvx agentpdf convert spec.pdf -o docs/reference
uvx agentpdf search -d docs/reference "attach request timer"

docs/reference/
├── AGENTS.md          # how agents should use this directory
├── search.sqlite      # full-text index over all documents
└── spec/
    ├── INDEX.md       # table of contents with page ranges and sizes
    ├── PAGES.md       # page → section, table and figure images
    ├── sections/      # Markdown, ≤ ~6k tokens per file, with page markers
    └── images/        # one PNG per table and figure

Requires uv (or pip install agentpdf). Runs locally on CPU, in seconds even for documents with hundreds of pages; no models or network access needed.

Using it with agents

Point the agent at the output. Add one line to your project's AGENTS.md or CLAUDE.md:

Reference documents (PDF specs) are in docs/reference/; see its AGENTS.md.

The generated AGENTS.md explains the layout and the search command in a few lines.

Or just ask. Agents that can run commands can do the conversion themselves: "Convert spec.pdf with uvx agentpdf (github.com/mensi/agentpdf) and use it to implement …"

Or install the skill (Claude Code), so agents convert and search PDFs on their own:

/plugin install agentpdf --marketplace mensi/agentpdf

On older versions: /plugin marketplace add mensi/agentpdf, then /plugin install agentpdf@agentpdf. The skill is a plain Agent Skill in plugins/agentpdf/skills/agentpdf, which you can also copy into ~/.claude/skills/ or another agent's skill directory.

How it works

• Text is extracted with PDFium in reading order; running headers, footers and printed tables of contents are dropped; paragraphs are re-flowed so phrases are searchable.
• Sections follow the PDF's bookmarks, or headings inferred from typography. Large sections are split at subheadings to fit the size budget.
• Tables and figures are not converted to Markdown tables, which is unreliable. Each is rendered as an image — the source of truth — plus a text transcription that keeps characters at their horizontal position.
• Search uses SQLite FTS5 (BM25 ranking, stemming); hits point to file, line, page and heading.

Only PDFs with a text layer are supported; scanned pages are rendered as images but not OCRed.

Options

agentpdf convert PDF... -o DIR [--max-tokens 6000] [--dpi 150]
                               [--page-images] [--split-pdf] [--no-index]
                               [--force]
agentpdf search QUERY [-d DIR] [-n 10] [--doc NAME] [--any]

--page-images also renders every page, --split-pdf writes one PDF per section, --force writes into an existing non-empty output directory. Converting again replaces a document's output.

Development

uv sync
uv run pytest
uv run ruff check . && uv run ruff format --check .

License

MIT